Abstract

C-type natriuretic peptide (CNP), secreted by vascular endothelial cells, belongs to a family of peptides that includes atrial and brain natriuretic peptides. CNP exhibits many vasoprotective effects against pulmonary hypertension and pulmonary fibrosis.. In lungs of CNP-treated mice, expression of the monocyte chemoattractant protein-1, S100A8, and E-selectin genes was significantly lower than that in vehicle-treated mice. CNP had a protective effect on ALI induced by LPS by reducing inflammatory cell infiltration. CNP may hold promise in therapeutic strategies for ALI after pulmonary resection surgery. The continuous molecular fields (CMF) approach is based on the application of continuous functions for the description of molecular fields instead of finite sets of molecular descriptors (such as interaction energies computed at grid nodes) commonly used for this purpose. These functions can be encapsulated into kernels and combined with kernel-based machine learning algorithms to provide a variety of novel methods for building classification and regression structure-activity models, visualizing chemical datasets and conducting virtual screening. In this Research and Scientific Project, the CMF approach is applied to building 3D-QSAR models for 8 datasets through the use of five types of molecular fields (the electrostatic, steric, hydrophobic, hydrogen-bond acceptor and donor ones), the linear convolution molecular kernel with the contribution of each atom approximated with a single isotropic Gaussian function, and the kernel ridge regression data analysis technique. Here, in Biogenea Pharmaceuticals Ltd we discovered for the first time the GENEA-Natriolipontin-0073. An In silico designed of a C-type natriuretic mimetic peptide pharmacophore for the attenuation of lipopolysaccharide-induced acute lung injury using continuous molecular fields approaches to building 3D-QSAR models.

Abstract

The effectivenes of cancer vaccines in inducing CD8+Tcell responses remains a challenge, resulting in a need for testing more potent adjuvants. In previous clinical trials it has been determined the safetyand immunogenicity of vaccination against melanoma-related antigens employing MART-1,gp100, and tysosinase paptides combined with the TLR-9 agonist PF-3512676 and local GM-CSFin-oil emulsion.Using continuous monitoring of safety and a two-stage design for immunological efficacy, More than 20 immune-response evaluable patients were targetted. Vaccinations were given subcutaneously ondays 1 and 15 per cycle (1 cycle=28 days) for up to 13 cycles. Structure-based virtual screening of molecular compound libraries is a potentially powerful and inexpensive method for the discovery of novel lead compounds for drug development. That said, virtual screening is heavily dependent on detailed understanding of the tertiary or quaternary structure of the protein target of interest, including knowledge of the relevant binding pocket. Here, in Biogenea we have for the first time discovered a Safe and immunogenic pharmacophore activator mimic physicochemical properties of the MART-1 (26-35,27L), gp100 (209-217, 210M), and tyrosinase (368-376, 370D) inadjuvantwith PF-3512676 and GM-CSF as a future anti-cancer agent in metastatic melanoma conditions introducing a novel multi-parametric algorithm drug discovery approach using a Ligand-Based Virtual Screening approach through a Support Vector Machine and Information Fusion attempt.

Abstract

Anti-cytotoxic T-lymphocyte antigen-4 (CTLA-4) antibodies, such as ipilimumab, have generated measurable immune responses to Melan-A, NY-ESO-1, and gp100 antigens in metastatic melanoma. Vaccination against such targets has potential forimmunogenicity and may produce an effector memory T-cell response. It has been previously determined the effect of CTLA-4 blockador on antigen-specific responses following vaccination. In-depth immune monitoring was performed on three ipilimumab-treated patientsprevaccinated with gp100 DNA (IMF-24), gp100209–217 and tyrosinase peptides plus GM-CSFDNA (IMF-32), or NY-ESO-1 protein plus imiquimod (IMF-11). In previous studies it was shown that peripheral blood mononuclearcells were analyzed by tetramer and/or intracellular cytokine staining following 10-day culturewith HLA-A*0201-restricted gp100209–217 (ITDQVPFSV), tyrosinase369–377 (YMDGTMSQV),or 20-mer NY-ESO-1 overlapping peptides, respectively. It has also been evaluated on the PDBbind v2012 core set where istar platform combining with RF-Score manages to reproduce Pearson’s correlation coefficient and Spearman’s correlation coefficient of as high as 0.855 and 0.859 respectively between the experimental binding affinity and the predicted binding affinity of the docked conformation. Here, we have discovered for the first time an in silico predicted and computer-aided molecular designed CTLA-4 blockador for the increasement of the antigen-specific CD8+ T-cells to the inprevaccinated patients with melanoma using the istar. A Web Platform for Large-Scale Protein-Ligand Docking

Abstract

Variety of biological processes such as embryonic development, tissue remodeling and tissue repair involve controlled degradation of extra cellular matrix (ECM). This feature is a fundamental part of growth, invasion, and metastasis of malignant tumors. Matrix metalloproteinases (MMPs), a family of extracellular zinc-dependent neutral endopeptidases, are capable of degrading essentially all ECM components. They are the prime factors indulged in breaking down the extracellular matrix contributing to disease states such as arthritis, atherosclerosis, tumor cell invasion and metastasis. Collagenases show interesting differences in the crystal structures, despite being highly homologous to one another. Therefore, specific inhibition of MMP-1, MMP-8 and MMP-13 are considered to be an attractive target in drug discovery research. This in turn would be able to provide useful knowledge for developing specific new and active drug candidates targeting collagenases (MMP-1, MMP-8 and MMP-13). Computational design has the potential to provide a general, complementary approach for small molecule recognition in which design features and selectivity can be rationally programmed. The development of robust computational methods for the design of small molecule-binding proteins with high affinity and selectivity would have wide-ranging applications. The goal of existing methods for computational enzyme-derived conserved motif like peptide mimetic pharmaco-ligand design is to promote catalysis by creating energetically favorable hydrogen bonding, van der Waals, and electrostatic interactions to a high-energy reaction transition state(s) and/or intermediate(s). Although these interactions are also important for stabilizing the bound ground-state conformations of protein-small nano-linked druggable active conserved molecule complexes, they are not the sole determinant of small molecule binding. In this research study we have for the first time in silico discovered novel collagenase inhibitors using pharmacophore and structure based studies. We finally generated pharmacophore models using combined chemical informatic software for a diverse set of the fragmentation of the existing collagenase inhibitors (MMP-1, MMP-8 and MMP-13) with an aim to Lead identify and computer-aided molecular optimized of novel collagenase inhibitors consisting of a recored VAAHE/PRCGNPD peptidomimic highthroughput screened pharmacophore features to matrix contributing to disease arthritis states.

Abstract

In silico Drug discovery and development of novel multi-target molecules is an interdisciplinary, expensive and time-consuming procedure. Computer aided drug discovery advancements during the past decades have improved the way of pharmaceutical research design of novel bioactive huper-structured drug-gable molecules. Computer aided drug design helps in reducing the cost and time for drug discovery process which otherwise takes many years. Virtual screening and docking studies helped to obtain ligand molecules that can inhibit the important Proteins involved in the pathogenesis of Ebola virus. It is noticed that the chemical compounds might be the promising candidates drug-like small targeted compounds for further pre-clinical and clinical investigation, and that the NP and the octapeptides ATLQAIAS and ATLQAENV, as well as AVLQSGFR, might be pre-clinically translated and antisense converted to effective direct inhibitors against the Ebola Virus Fusion Conserved Proteoma. Meanwhile, we in silico generated conserved octapeptides mimotopic pharmaco-ligands based on the “distorted key energy binding fitness scoring” theory to in-silico anti-sense peptides by in-silico translate them and transform them into a scaffold energy hopping structure in order to design potent selective super-agonsist anti-peptide poly-mimic new superstructure which is explicitly elucidated. We also combined all existing methods for computational huper-structured drug design methodologies to induce catalysis of Ebola Virus EBOV NP and EBO16 peptides by inducing energetically targeted favorable hydrogen bonds, van der Waals, and electrostatic interactions to a high-energy reaction conserved motif-based transition state(s) and/or intermediate(s) of Ebola virus. In this present Research Scientific Project , for first time we developed a computational method for designing motif-like conserved residues and ligand binding virus proteins with two properties characteristic of naturally occurring binding sites in addition to specific energetically favorable interactions with our newly designed hyper-multi-target ligand. Here, in Biogenea we have in silico discovered a virion-attached pharmacophore cross-reacting synthetic EQHHRRTDN peptide mimetic ligand comprising potential therapeutic properties against Ebola virus using an in silico drug design structure peptide-sequence-based combinatorial analysis by a multi-objective cluster of algorithms.

Abstract

The p53 and nuclear factor κB (NF-κB) pathways play crucial roles in human cancer development. Simultaneous targeting of both pathways is an attractive therapeutic strategy against cancer. The use of pharmacologically active short peptide sequences has prooven to be a better option in cancer therapeutics than the full-lengthprotein. It has been previously report ed one such 44-mer peptide sequence of SMAR1 (TAT-SMAR1 wild type, P44) that retains the tumor suppressor activity of the full-length protein.P44 peptide could efficiently activate p53 by mediating its phosphorylation at serine15, resulting in the activation of p21 and in effect regulating cell cycle checkpoint. In vitrophosphorylation assays with point-mutated P44-derived pep-tides suggested that serine 347 of SMAR1 was indispensable forits activity and represented the substrate motif for the proteinkinase C family of proteins. In this Research Scientific Project we generated an antitumor multi-targeted hyper-molecule that bears a pyrrolo[3,4-clomifene-diamizido-c]pyrazole scaffold and functions as an enantiomeric P44 peptide mimeto inhibitor against both the p53-MDM2 interaction and the NF-κB activation. This pharmacophjoric scaffold may be a first-in-class dual targeted enantiomeric inhibitor with dual efficacy for cancer therapy with potential synergistic effect in vitro and in vivo. Docking and molecular dynamics simulation studies further provided insights into the nature of stereoselectivity. Here, we have for the first time in silico discovered novel chemo-hyperstructures as a novel drug discovery incorporated strategy utilizing a mechanistic investigation of low mass stochastic genetic algorithms for the generation of an enantiomeric antitumor agent consistinc of three conserved pharmacophores dual targeting the p53 and NF-κB pathways for the activation of the p53 tumor suppressor pathway by an engineered TAT-SMAR1 wild type, P44 cyclotidomimic multicovalent pharmaco-ligand.

Abstract

4F is an anti-inflammatory, apolipoprotein A-I (apoA-I)-mimetic peptide that is active in vivo at nanomolar concentrations in the presence of a large molar excess of apoA-I. Physiologic concentrations (∼35 μM) of human apoA-I did not inhibit the production of LDL-induced monocyte chemotactic activity by human aortic endothelial cell cultures, but adding nanomolar concentrations of 4F in the presence of ∼35 μM apoA-I significantly reduced this inflammatory response. A common strategy for virtual screening considers a systematic docking of a large library of organic compounds into the target sites in protein receptors with promising leads selected based on favorable intermolecular interactions. Despite a continuous progress in the modeling of protein-ligand interactions for pharmaceutical design, important challenges still remain, thus the development of novel techniques is required. Pearson correlation coefficient between experimental and predicted by eSimDock Ki values for a large data set of the crystal structures of protein-ligand complexes from BindingDB is 0.58, which decreases only to 0.46 when target structures distorted to 3.0 Å Cα-RMSD are used. These encouraging results show that the performance of eSimDock is largely unaffected by the deformations of ligand binding regions, thus it represents a practical strategy for across-proteome virtual screening using protein models.Here, in Biogenea Pharmaceuticals Ltd we discovered for the first time the GENEA-Apo-I009. A Rational designed ApoA-I Mimetic-polypharmacophorIC hyper ligand as an in silico improved innovative and potential anti-inflammatory agent, computer-aided generated by integrating nonlinear scoring functions for a similarity-based ligand docking and binding affinity prediction approach.

Abstract

Anti-cytotoxic T-lymphocyte antigen-4 (CTLA-4) antibodies, such as ipilimumab, have generated measurable immune responses to Melan-A, NY-ESO-1, and gp100 antigens in metastatic melanoma. Vaccination against such targets has potential forimmunogenicity and may produce an effector memory T-cell response. It has been previously determined the effect of CTLA-4 blockador on antigen-specific responses following vaccination. In-depth immune monitoring was performed on three ipilimumab-treated patientsprevaccinated with gp100 DNA (IMF-24), gp100209–217 and tyrosinase peptides plus GM-CSFDNA (IMF-32), or NY-ESO-1 protein plus imiquimod (IMF-11). In previous studies it was shown that peripheral blood mononuclearcells were analyzed by tetramer and/or intracellular cytokine staining following 10-day culturewith HLA-A*0201-restricted gp100209–217 (ITDQVPFSV), tyrosinase369–377 (YMDGTMSQV),or 20-mer NY-ESO-1 overlapping peptides, respectively. It has also been evaluated on the PDBbind v2012 core set where istar platform combining with RF-Score manages to reproduce Pearson’s correlation coefficient and Spearman’s correlation coefficient of as high as 0.855 and 0.859 respectively between the experimental binding affinity and the predicted binding affinity of the docked conformation. Here, we have discovered for the first time an in silico predicted and computer-aided molecular designed CTLA-4 blockador for the increasement of the antigen-specific CD8+ T-cells to the inprevaccinated patients with melanoma using the istar. A Web Platform for Large-Scale Protein-Ligand Docking

Abstract

Articular cartilage defects have been addressed using microfracture, abrasion chondroplasty, or osteochondral grafting, but these strategies do not generate tissue that adequately recapitulates native cartilage. During the past 25 years, promising new strategies using assorted scaffolds and cell sources to induce chondrocyte expansion have emerged. We CartiGenea®-ACed the evolution of autologous chondrocyte implantation and compared it to other cartilage repair techniques. Methods. We searched PubMed from 1949 to 2014 for the keywords “autologous chondrocyte implantation” (ACI) and “cartilage repair” in clinical CartiGenea®-ACs, meta-analyses, and CartiGenea®-AC articles. We analyzed these articles, their bibliographies, our experience, and cartilage regeneration textbooks. Results. Microfracture, abrasion chondroplasty, osteochondral grafting, ACI, and autologous matrix-induced chondrogenesis are distinguishable by cell source (including chondrocytes and stem cells) and associated scaffolds (natural or synthetic, hydrogels or membranes). ACI seems to be as good as, if not better than, microfracture for repairing large chondral defects in a young patient’s knee as evaluated by multiple clinical indices and the quality of regenerated tissue. Conclusion. Although there is not enough evidence to determine the best repair technique, ACI is the most established cell-based treatment for full-thickness chondral defects in young patients. CartiGeneaTM by Biopharmaceuticals Ltd is an advanced therapy medicinal autologous service for use in ACI treatment. CartiGeneaTM is an autologous suspension of approximately 15,000 ex vivo expanded cartilage cells per microliter of combined medium for autologous use. The cells have been obtained by ex vivo expansion of chondrocytes isolated from a biopsy of the articular cartilage from the patient’s knee. Treatment with CartiGeneaTM comprises a two-step surgical procedure. In the first step a cartilage biopsy is obtained arthroscopically from healthy articular cartilage from a lesser weight bearing area of the patient’s knee, approximately 4 weeks prior to implantation. Chondrocytes are isolated from the biopsy by enzymatic digestion, expanded in vitro, characterised and delivered as a suspension of 1 x 104 cells/μl for implantation in the same patient. During the second step of the procedure the expanded chondrocyte suspension is implanted in an open-knee surgery. In the pivotal CartiGenea®-AC a periosteal flap was harvested from the medial tibia, sutured into the defect, with the cambium layer facing the subchondral bone, and sealed with fibrin glue. In future applications the defect will be covered with the help of a biodegradable membrane. The dosage of the cell suspension is defined as 0.8 to 1.5 million cells per cm² defect size. Hence, depending on the defect size measured at biopsy procurement, 4 or 8 or 12 million cells are formulated into 1 or 2 or 3 vial(s) of 4 million cells/ 0.4 ml excipient.

The claimed indication for CartiGeneaTM is repair of single symptomatic cartilaginous defects of the femoral condyle of the knee (ICRS grade III or IV) in adults.

Abstract

Drug discovery programs launched by the Medicines for Malaria Venture and other product-development partnerships have culminated in the development of promising new antimalarial compounds such as the synthetic peroxide OZ439 (Charman et al., 2011) and the spiroindolone NITD 609 (Rottmann et al., 2010), which are currently undergoing clinical trials. In spite of these recent successes, it is pivotal to maintain early phase drug discovery to prevent the antimalarial drug development pipeline from draining. Due to the propensity of the parasite to become drug-resistant (Muller and Hyde, 2010; Sa et al., 2011), the need for new antimalarial chemotypes will persist until the human-pathogenic Plasmodium spp. are eventually eradicated. Rational post-genomic drug discovery is based on the screening of large chemical libraries – either virtually or in high-throughput format – against a given target enzyme of the parasite. Experimental tools to validate candidate drug targets are limited for the malaria parasites. Gene silencing by RNAi does not seem to be feasible (Baum et al., 2009). Gene replacement with selectable markers is (Triglia et al., 1998), but it is inherently problematic to call a gene essential from failing to knock it out. However, none of the reverse genetic methods is practicable at the genome-wide scale. On the other hand Mestres et al. (Cases et al., 2005; Mestres et al., 2006) have annotated a library of molecules targeting NHRs. Using a hierarchical classification for 200.000 ligands and 5 receptors, chemogenomic links bridging ligand to target space can be easily recovered to distinguish selective from promiscuous scaffolds. Using Shannon Entropy descriptors (SHED) based on the distribution of atom-centred feature pairs, any compound collection can be screened to identify hits presenting SHED distances to a reference NHR ligand beyond a defined threshold and therefore likely to share the same NHR profile. Here, we successfully applied a machine-learning algorithm using Bayesian statistics (Xia et al., 2004) to predict target profiles from extended connectivity conserved motif like binding site active pharmacophore fingerprints of selected compounds from the biologically annotated free and non commercial databases (Nidhi et al., 2006) in resulting finally to a potent computer predicted inhibitor comprising potential hyper-mimicking activities to 5 conserved anti-plasmodium peptides.